Label-Free AI at scale for enterprises.
HephIA helps your organization manage modern data challenges by storing and organizing large and complex data without having to label your data in advance.
And more !
Tailored for Big Data
ON TABULAR & TEMPORAL DATA
Multivariate & Univariate
From research laboratory to industry
The development of AI tools proposed by the company is based on a long-standing laboratory history around the team research in scalable unsupervised AI, notably within the Computer science laboratory (LIPN, UMR CNRS 7030) of Sorbonne Paris Nord university (USPN).
The work of the group is the result of numerous research and industrial partnerships on very ambitious projects with contributions to various fields including: automotive, aeronautics, survey analysis, bioinformatics, information retrieval and the environment.
A tool complementing market tools for the industry
Scalable Unsupervised learning is a subfield of AI rich in essential and powerful models to tackle large-scale AI projects. This family of technologies enables large amounts of data, not easily understandable by human operators in their raw form, to be organized and abstracted, providing a human expert with a global overview and understanding of their data, without requiring the definition of labels or tags beforehand. These techniques can also be used as an efficient preliminary phase of supervised AI / label prediction pipelines.
Who are we ?
HephIA was born from the association between Gaël Beck, Anthony Coutant and Mustapha Lebbah following partnerships involving the LIPN lab.
Ph.D. in large-scale AI, and expert in functional object programming, Gaël loves Scala, which he uses in all his projects. His field experience as a Machine Learning engineer for several years at Kameleoon allowed him to successfully lead projects mixing state-of-the-art AI, scalability on big data, and industrialization of concrete solutions.
With a Ph.D. in AI and a dual profile in software engineering for business information systems management, Anthony has developed a sensitivity for the development of efficient software tools for AI. He has experience of more than 7 years on ambitious AI projects, both in academic and industrial contexts.
Mustapha Lebbah has been teaching and researching in AI since 2005, and is a member of the A3 team specialized in Machine Learning in the LIPN lab. An expert in large-scale unsupervised AI. He is the author of multiple publications and has supervised nearly fifteen doctoral students on the subject. His research history is marked by numerous academic and industrial partnerships on very ambitious projects.